Project description
Cyber secure and flexible vehicle-to-grid connectivity
Vehicle-to-grid technology allows electric vehicles (EVs) to send unused energy from their batteries back to the power grid, enhancing grid flexibility. However, this increased connectivity also exposes the power system to significant cybersecurity threats that can lead to disruptions. Supported by the Marie Skłodowska-Curie Actions programme, the TRUST-V2G project aims to create a secure, efficient and privacy-protected framework for bidirectional EV charging, leveraging advanced AI and real-world operational testing. The framework will consist of a comprehensive defence system that integrates three key technologies: privacy-preserving AI to detect network threats and ensure data protection, adaptive graph modelling to anticipate evolving attack patterns, and intelligent, multi-agent defences to maintain grid stability, safety and performance.
Objective
The European Union’s transition to a climate-neutral energy system depends on large-scale integration of renewable energy and flexible infrastructures. Vehicle-to-Grid (V2G) technology, which enables electric vehicles to both consume and supply electricity, can provide critical flexibility but also exposes the power system to new cybersecurity risks. The TRUST-V2G project will develop a secure, privacy-preserving, and efficient V2G framework that combines advanced artificial intelligence with real-world validation in European living labs. The research introduces three integrated innovations: (i) Federated Privacy-Preserving Intelligence to detect cyber threats across heterogeneous V2G networks while guaranteeing data protection; (ii) Adaptive Temporal Graph Neural Networks to model evolving attack patterns and anticipate cascading risks; and (iii) Multi-Agent Reinforcement Learning-based Defense Orchestration to optimize grid resilience, safety, and performance under adversarial conditions. TRUST-V2G will be validated at Linköping University Vehicle Lab with over 20 operational V2G systems, advancing technology readiness from TRL 3 to 5. This project will enhance the scientific skills and innovation capability, expand research horizons, and establish research collaborations with both the academic & non-academic sectors of the applicant. The fellowship will train the researcher in federated learning, graph reasoning, and reinforcement learning, while transferring expertise in control theory and intelligent coordination to the host institutions. By delivering a scalable framework that strengthens digital trust, enhances grid stability, and supports inclusive energy security, TRUST-V2G will directly contribute to the European Union’s goals under the Green Deal, the Cyber Resilience Act, and Horizon Europe’s priorities for secure and sustainable energy systems.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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(opens in new window) HORIZON-MSCA-2025-PF
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581 83 Linkoping
Sweden
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